يعرض 1 - 20 نتائج من 21 نتيجة بحث عن '(( binary more lead optimization algorithm ) OR ( binary image codon optimization algorithm ))', وقت الاستعلام: 0.34s تنقيح النتائج
  1. 1

    The Pseudo-Code of the IRBMO Algorithm. حسب Chenyi Zhu (9383370)

    منشور في 2025
    "…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"
  2. 2

    IRBMO vs. meta-heuristic algorithms boxplot. حسب Chenyi Zhu (9383370)

    منشور في 2025
    "…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"
  3. 3

    IRBMO vs. feature selection algorithm boxplot. حسب Chenyi Zhu (9383370)

    منشور في 2025
    "…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"
  4. 4

    Pseudo Code of RBMO. حسب Chenyi Zhu (9383370)

    منشور في 2025
    "…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"
  5. 5

    P-value on CEC-2017(Dim = 30). حسب Chenyi Zhu (9383370)

    منشور في 2025
    "…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"
  6. 6

    Memory storage behavior. حسب Chenyi Zhu (9383370)

    منشور في 2025
    "…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"
  7. 7

    Elite search behavior. حسب Chenyi Zhu (9383370)

    منشور في 2025
    "…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"
  8. 8

    Description of the datasets. حسب Chenyi Zhu (9383370)

    منشور في 2025
    "…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"
  9. 9

    S and V shaped transfer functions. حسب Chenyi Zhu (9383370)

    منشور في 2025
    "…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"
  10. 10

    S- and V-Type transfer function diagrams. حسب Chenyi Zhu (9383370)

    منشور في 2025
    "…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"
  11. 11

    Collaborative hunting behavior. حسب Chenyi Zhu (9383370)

    منشور في 2025
    "…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"
  12. 12

    Friedman average rank sum test results. حسب Chenyi Zhu (9383370)

    منشور في 2025
    "…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"
  13. 13

    IRBMO vs. variant comparison adaptation data. حسب Chenyi Zhu (9383370)

    منشور في 2025
    "…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"
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    Variable Selection with Multiply-Imputed Datasets: Choosing Between Stacked and Grouped Methods حسب Jiacong Du (12035845)

    منشور في 2022
    "…Building on existing work, we (i) derive and implement efficient cyclic coordinate descent and majorization-minimization optimization algorithms for continuous and binary outcome data, (ii) incorporate adaptive shrinkage penalties, (iii) compare these methods through simulation, and (iv) develop an R package <i>miselect</i>. …"
  17. 17

    PathOlOgics_RBCs Python Scripts.zip حسب Ahmed Elsafty (16943883)

    منشور في 2023
    "…</p><p dir="ltr">In terms of classification, a second algorithm was developed and employed to preliminary sort or group the individual cells (after excluding the overlapping cells manually) into different categories using five geometric measurements applied to the extracted contour from each binary image mask (see PathOlOgics_script_2; preliminary shape measurements). …"
  18. 18

    Supplementary Material 8 حسب Nishitha R Kumar (19750617)

    منشور في 2025
    "…In AMR studies, datasets often contain more susceptible isolates than resistant ones, leading to biased model performance. …"
  19. 19

    Predictive Analysis of Mushroom Toxicity Based Exclusively on Their Natural Habitat. حسب Enrico Bertozzi (22461709)

    منشور في 2025
    "…<br>The consistency of the results across different kernels demonstrates that the information contained in the habitat, by itself, leads to a very simple optimal decision rule (mostly the prediction of the most frequent class per habitat), which cannot be improved solely by model adjustments. …"
  20. 20

    Data_Sheet_1_The impact of family urban integration on migrant worker mental health in China.docx حسب Xiaotong Sun (6535064)

    منشور في 2024
    "…The results of this study lead the authors to recommend formulating a family-centered policy for migrant workers to reside in urban areas, optimizing the allocation of medical resources and public services, and improving family urban integration among migrant workers in order to avoid mental health problems in the process of urban integration.…"